Registration:Categories

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Slicer Registration Case Library: Examples & Tutorials

looking for a set of features: 3DSlicer Registration Feature/Decision Matrix Registration DecisionMatrix.png

  • the matrix below shows which modules support which feature, intended to help you if looking for a method with a particular combination of features.
  • if you would like to see additional criteria or a new module is not yet listed, please let us know: mailto:slicer-users at bwh.harvard.edu
  • see here for an interactive method selection tool
3DSlicer Registration Feature/Decision Matrix

looking for Speed Registration Speed icon.png

looking for Robustness and/or Precision Registration Precision icon.png

  • The Expert Automated Registration module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest
  • The Robust Multiresolution Affine Registration module performs robust automated affine image registration employing a multi-resolution scheme.
  • The Plastimatch module performs automated registration of images from rigid to affine to non-rigid. As a unique feature it provides non-rigid deformation from fiducials, which can be used to "edit/repair" a registration.
  • The AC-PC Transform module is used to orient brain images along the anterior- and posterior commissure and midline. Within the accuracy of the manually chosen anatomical landmarks this alignment tends to be very robust.

choose by DOF Registration HLogo DOF.png

  • non rigid 27- 100s DOF:
    • The Fast Nonrigid BSpline Registration module performs non-rigid automated image registration.
    • The BAINSfit module includes a registration based on a Bspline transform. Initially designed for but not limited to brain images. Also includes many options such as masking support.
  • non rigid (fluid) >100 DOF
    • The BRAINSDemonWarp module performs automated registration of brain MRI based on an optic flow mechanism. Deformations here are significantly more "fluid" (i.e. have more DOF and are less constrained) than for the nonrigid BSpline method.
    • The Plastimatch module performs automated registration of images from rigid to affine to non-rigid. As a unique feature it provides non-rigid deformation from fiducials, which can be used to "edit/repair" a registration.
    • The HAMMER Module performs elastic (non-rigid) alignment of brain images of different individuals based on tissue class segmentation and intensity (experimental stage).

choose by Datatype Registration HLogo Datatype.png

  • images, same modality: The Expert Automated Registration module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest
  • images, different modality: The Expert Automated Registration module performs automated image registration, rigid to affine, based on image intensity similarities. Select Mutual Information as cost function.
  • surfaces: The Surface Registration module performs automated registration of surfaces (not images). This is useful if image data directly is unreliable, but surfaces can be produced from segmentations that provide good information about desired alignment.
  • fiducials: The Fiducial Alignment module can align images based on pairs of manually selected fiducial points (rigid and affine). Two sets of fiducials (fiducial lists) are required, forming matching pairs to be aligned. Use the Fiducials module to create fiducial lists. The AC-PC Transform module is also a special form of fiducial registration, used to orient brain images along the anterior- and posterior commissure and midline.

looking for Brain Image Registration Registration HLogo Brain.png

  • The AC-PC Transform module is used to orient brain images along predefined anatomical landmarks: (manually defined) fiducials for the inter-hemispheral midline, anterior- and posterior commissure are used to align an image such that these landmarks become vertical and horizontal, respectively.
    • The BAINSfit module includes a registration based on a Bspline transform. Initially designed for but not limited to brain images. Also includes many options such as masking support.
  • The BRAINSDemonWarp module performs automated registration of brain MRI based on an optic flow mechanism. Deformations here are significantly more "fluid" (i.e. have more DOF and are less constrained) than for the nonrigid BSpline method.
  • The HAMMER Module performs elastic (non-rigid) alignment of brain images of different individuals based on tissue class segmentation and intensity (experimental stage).


looking for Tools to Resample Data Registration Resample icon.png

  • see the Overview of Resampling Tools for all available resampling methods, including tools to resample in place (e.g. change resolution or voxel anisotropy etc.)

looking for Tools for Preparing Data for Registration Registration Masking icon.png

  • Intensity Normalization & Filtering
Intensity corrections are often the first processing step of choice. MRI bias field inhomogeneities can adversely affect registration accuracy and stability, as can large differences in the intensity ranges between the two images, or large amounts of noise
  • Masking
Masks are an important component of many registration tasks. They allow to focus the algorithm on the region of interest (ROI) that is to be registered and prevent it from being distracted by image content outside this ROI.